:py:mod:`simind_io`
===================

.. py:module:: simind_io


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   simind_io.get_header_value
   simind_io.get_projections_from_single_file
   simind_io.get_projections
   simind_io.get_source_detector_distances
   simind_io.get_meshgrid



Attributes
~~~~~~~~~~

.. autoapisummary::

   simind_io.relation_dict


.. py:data:: relation_dict

   

.. py:function:: get_header_value(list_of_attributes, header, dtype = np.float32, split_substr=':=', split_idx=-1, return_all=False)

   Finds the first entry in an Interfile with the string ``header``

   :param list_of_attributes: Simind data file, as a list of lines.
   :type list_of_attributes: list[str]
   :param header: The header looked for
   :type header: str
   :param dtype: The data type to be returned corresponding to the value of the header. Defaults to np.float32.
   :type dtype: type, optional

   :returns: The value corresponding to the header (header).
   :rtype: float|str|int


.. py:function:: get_projections_from_single_file(headerfile)

   Gets projection data from a SIMIND header file.

   :param headerfile: Path to the header file
   :type headerfile: str
   :param distance: The units of measurements in the SIMIND file (this is required as input, since SIMIND uses mm/cm but doesn't specify). Defaults to 'cm'.
   :type distance: str, optional

   :returns: Simulated SPECT projection data.
   :rtype: (torch.Tensor[1, Ltheta, Lr, Lz])


.. py:function:: get_projections(headerfiles)

   Obtains projection PSF data from a list of headerfiles and concatenates them together

   :param headerfiles: List of length Ld corresponding to all projections at different source-detector distances.
   :type headerfiles: str | Sequence[str]

   :returns: Output tensor of PSF data at each source-detector distance
   :rtype: torch.Tensor[Ld,Lx,Ly]


.. py:function:: get_source_detector_distances(resfiles)

   Obtains the source-detector distance from a list of resfiles

   :param resfiles: List of .res files (of length Ld) corresponding to each simulated PSF projection
   :type resfiles: str

   :returns: List of source-detector distances
   :rtype: torch.Tensor[Ld]


.. py:function:: get_meshgrid(resfiles, device='cpu')

   Obtains a meshgrid of the x and y coordinates correpsonding to the PSF data simulated

   :param resfiles: List of .res files (of length Ld) corresponding to each simulated PSF projection
   :type resfiles: str
   :param device: Device to place the output projection data on. Defaults to 'cpu'.
   :type device: str, optional

   :returns: Meshgrid of x and y coordinates
   :rtype: tuple[torch.Tensor, torch.Tensor]